ENERGY ACCUMULATION FROM SOLAR PANELS AND FORECASTING MODELS FOR ENERGY PRODUCTION USING ARTIFICIAL INTELLIGENCE

This paper explores the process of energy accumulation from solar panels and the possibilities of analyzing energy production through forecasting models using artificial intelligence. The efficiency of photovoltaic systems is influenced by various external factors, such as solar radiation, temperature, dust levels, and seasonal variations. Considering these factors, the feasibility of predicting energy output using artificial neural networks, regression models, and machine learning algorithms is examined. Furthermore, the efficiency of modern energy storage technologies like lithium-ion batteries and supercapacitors is discussed. Research shows that implementing AI-based forecast models helps to properly manage energy reserves and reduce grid load.